A new robust equation for shear strength of GFRP-RC deep beams using hybrid experimental and synthetic data based-FE quasi-static analysis procedure

纤维增强塑料 结构工程 极限抗拉强度 抗压强度 参数统计 材料科学 剪切(地质) 复合材料 数学 工程类 统计
作者
Osama Ali,Aya Abbas,Eehab Khalil,David Bigaud
出处
期刊:Engineering Structures [Elsevier BV]
卷期号:293: 116652-116652
标识
DOI:10.1016/j.engstruct.2023.116652
摘要

The main objective of this article is to propose a new, more robust, and comprehensive design equation for Glass-Fiber-Reinforced-Polymer (GFRP) reinforced concrete (RC) Deep Beams (DBs). The investigation is based on a numerical model using Quasi-Static Two-Dimensional FE simulation of GFRP-RC DBs. The numerical model is validated by calibrating four parameters (concrete dilatation angle ψ, concrete tensile strength fct, fracture energy Gf, mesh size) against data from ten full-scale experiments on GFRP-RC DBs available in the literature. Additionally, a numerical parametric study based on a full factorial design with 5 factors (and between 2 and 5 modalities) is conducted using the validated quasi-static FE model, which includes 360 large-scale GFRP-RC DBs. The impacts of primary design variables on the concrete contribution Vc to the shear capacity of GFRP-RC DBs are assessed. The effects of various geometrical and mechanical variables, such as cross-sectional dimensions (width b × height H), concrete compressive strength grade (fc), GFRP properties (modulus Ef, and strength ffu), GFRP reinforcement ratio (ρf), and shear span to depth ratios (a/df), are examined to understand the shear behavior of GFRP-RC DBs. The numerical simulations demonstrate that the proposed FE model accurately captures the behavior of GFRP-RC DBs. Building upon these findings, a new shear design equation is proposed for DBs, and its accuracy and robustness are compared with five established international design codes (ACI-440.1R-15, ISIS-Canada, CAN/CSA-S806-12, JSCE-1997, and BS-8110). The existing design codes significantly underestimate the concrete contribution to shear capacity, leading to uneconomical designs. In contrast, the new design equation provides a fair prediction of Vc, with a standard error of 7.734 % and 20.84 % compared to the FE and experimental datasets, respectively. This represents a substantial improvement over the existing design guides.
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